Probabilistic predictive warning system for process operations

过程操作的概率预测预警系统

• 批准号: RGPIN-2019-04122
• 负责人: Ahmed, Salim
• 金额: $ 2.04万
• 依托单位: Memorial University of Newfoundland
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=682708
• 关键词: Probabilistic; predictive; warning; system; process

This program aims to develop a probabilistic predictive approach to the design and management of early warning systems used in process industries. The special features and novelty of the proposed approach is in the use of probabilistic models for alarm annunciation and the use of risk in every stage of warning design, namely, allocation, annunciation, prioritization and management. In addition, predictions will be used for issuing warnings. ***Industries significantly benefit from using predictions for control. On the other hand, considerable resources are used for risk assessment. However, current alarm systems are not risk-based; use of predictions is also restricted. Research efforts are required to make plant alarm systems an effective tool in preventing accidents. ***We plan to develop a comprehensive early warning system based on quantified risk and prediction of events from plant data. The current plant alarm systems use a deterministic setting where abnormality is described without any reference to its likelihood. Our objective is to develop tools to describe unwanted events in terms of likelihood and perform diagnosis by considering a set of possible combinations of failures that explain the observations. Methodologies will be developed to quantify uncertainties with plant models which arise from assumptions on model structures and noises in process data. Uncertainties associated with risk models will also be developed. Correlations and dependencies among events as well as their consequences will be quantified and taken into account in the design of warning system. We also want to propose an alarm design philosophy to complement the existing standards in incorporating risk. A prototype alarm system will be developed that will be integrate-able with the existing plant alarm systems. The new system will be tested in pilot plants and industrial settings.***Process industries are in dire need of an improved alarm system. Operators are often overwhelmed by alarms and are unable to perform their main responsibilities. Risk is a measure that is well understood and highly valued. Hence, the developed methodology is expected to find widespread utility in process industries.***By developing technologies and tools that ensure smooth, accident-free operation of industrial plants, this program will contribute directly to the productivity of the industrial sector. Thus it will help to save billions of dollars in losses caused by abnormal situations in industries.***Along with the development of tools and methods, a number of highly qualified personnel will be trained in this program. The HQP will be trained on developing the tools as well as its implementation to real plants; thus the HQP will be valuable assets for the concerned industry. Finally, the developed methods will be useful for risk assessment in general with applications outside process facilities, e.g. for health monitoring, economic activities and natural disasters.***********

该计划旨在开发一种概率预测方法来设计和管理流程工业中使用的预警系统。该方法的特点和新颖之处在于使用概率模型进行警报通告以及在警报设计的每个阶段（即分配、通告、优先级和管理）中使用风险。此外，预测将用于发出警告。 ***使用预测进行控制使各行业受益匪浅。另一方面，大量资源用于风险评估。然而，当前的警报系统并不是基于风险的；预测的使用也受到限制。需要进行研究以使工厂报警系统成为预防事故的有效工具。 ***我们计划开发一个基于量化风险和工厂数据事件预测的综合预警系统。当前的工厂报警系统使用确定性设置，在描述异常时不考虑其可能性。我们的目标是开发工具来描述不需要的事件的可能性，并通过考虑一组可能的故障组合来解释观察结果来执行诊断。将开发方法来量化工厂模型的不确定性，这些不确定性是由于模型结构和过程数据中的噪声的假设而产生的。还将开发与风险模型相关的不确定性。事件之间的相关性和依赖性及其后果将被量化，并在预警系统的设计中得到考虑。我们还想提出一种警报设计理念，以补充纳入风险的现有标准。将开发一个原型报警系统，该系统可与现有工厂报警系统集成。新系统将在试点工厂和工业环境中进行测试。***过程工业迫切需要改进的报警系统。操作员常常被警报淹没，无法履行其主要职责。风险是一种众所周知且高度重视的衡量标准。因此，所开发的方法预计将在过程工业中得到广泛应用。***通过开发确保工厂平稳、无事故运行的技术和工具，该计划将直接提高工业部门的生产力。这将有助于挽救因行业异常情况而造成的数十亿美元的损失。***随着工具和方法的发展，该计划将培训一批高素质人才。 总部将接受有关开发工具及其在实际工厂中实施的培训；因此，总部基地将成为相关行业的宝贵资产。最后，所开发的方法将可用于工艺设施外部应用的一般风险评估，例如用于健康监测、经济活动和自然灾害。************